Chronic disease management in patients with intellectual disabilities: a matched study in Dutch general practice.

BACKGROUND: Disease management programmes (DMPs) aim to deliver standardised, high- quality care to patients with chronic diseases. Although chronic diseases are common among people with intellectual disabilities (ID), this approach may be suboptimal for meeting their care needs. AIM: To examine differences between patients with and without ID who have a chronic illness in DMP enrolment and disease monitoring in Dutch general practice. DESIGN AND SETTING: Observational study utilising the Nivel Primary Care Database (2015-2018) comparing patients with ID and cardiovascular disease, diabetes mellitus, or chronic obstructive pulmonary disease (COPD) with matched (1:5) controls with these conditions but without ID. METHOD: Using conditional logistic regression, enrolment in DMP per chronic disease was examined and differences tested between groups in the frequencies of consultations, medication prescriptions, and routine examinations. RESULTS: A total of 2653 patients with chronic illness with ID were matched with 13 265 controls without ID. Patients with both diabetes mellitus and ID were more likely than controls to be enrolled in DMP (odds ratio [OR] = 1.44, 95% confidence interval [CI] = 1.27 to 1.64). Independent of DMP enrolment, patients with chronic illness with ID were more likely than controls to have frequent consultations. Patients with both diabetes mellitus and ID and patients with both COPD and ID who were not enrolled in DMPs had more medication prescriptions than non-enrolled patients with diabetes or COPD but without ID (OR = 1.46, 95% CI = 1.10 to 1.95; OR = 1.28, 95% CI = 0.99 to 1.66, respectively). Most patients with ID and their controls enrolled in DMPs received routine examinations at similar frequencies. CONCLUSION: Although DMPs do not specifically address the needs of patients with both chronic illness and ID, these patients do not seem underserved in the management of chronic diseases in terms of consultation, medication, and tests.

Prognostic factors for persistent fatigue after COVID-19: a prospective matched cohort study in primary care.

BACKGROUND: Persistent fatigue after COVID-19 is common; however, the exact incidence and prognostic factors differ between studies. Evidence suggests that age, female sex, high body mass index, and comorbidities are risk factors for long COVID. AIM: To investigate the prevalence of persistent fatigue after COVID-19 in patients with a mild infection (managed in primary care) during the first wave of the pandemic and to determine prognostic factors for persistent fatigue. DESIGN AND SETTING: This was a prospective cohort study in Dutch general practice, combining online questionnaires with data from electronic health records. METHOD: Patients who contacted their GP between March and May 2020 and were diagnosed with COVID-19 during the first wave of the pandemic were included. Patients were matched to controls without COVID-19 based on age, sex, and GP practice. Fatigue was measured at 3, 6, and 15 months, using the Checklist of Individual Strength. RESULTS: All the participants were GP attendees and included 179 with suspected COVID-19, but who had mild COVID and who had not been admitted to hospital with COVID, and 122 without suspected COVID-19. Persistent fatigue was present in 35% (49/142) of the suspected COVID-19 group and 13% (14/109) of the non-COVID-19 group (odds ratio 3.65; 95% confidence interval = 1.82 to 7.32). Prognostic factors for persistent fatigue included low education level, absence of a partner, high neuroticism (using the Eysenck Personality Questionnaire Revised-Short Form), low resilience, high frequency of GP contact, medication use, and threatening experiences in the past. The latter three factors appeared to be prognostic factors for persistent fatigue specifically after COVID-19 infection. CONCLUSION: GP patients with COVID-19 (who were not admitted to hospital with COVID) have a fourfold higher chance of developing persistent fatigue than GP patients who had not had COVID-19. This risk is even higher in psychosocially vulnerable patients who had COVID-19.

Performance of the SCORE and Globorisk cardiovascular risk prediction models: a prospective cohort study in Dutch general practice.

BACKGROUND: GPs frequently use 10-year-risk estimations of cardiovascular disease (CVD) to identify high- risk patients. AIM: To assess the performance of four models for predicting the 10-year risk of CVD in Dutch general practice. DESIGN AND SETTING: Prospective cohort study. Routine data (2009- 2019) was used from 46 Dutch general practices linked to cause of death statistics. METHOD: The outcome measures were fatal CVD for SCORE and first diagnosis of fatal or non- fatal CVD for SCORE fatal and non-fatal (SCORE- FNF), Globorisk-laboratory, and Globorisk-office. Model performance was assessed by examining discrimination and calibration. RESULTS: The final number of patients for risk prediction was 1981 for SCORE and SCORE-FNF, 3588 for Globorisk-laboratory, and 4399 for Globorisk- office. The observed percentage of events was 18.6% (n = 353) for SCORE- FNF, 6.9% (n = 230) for Globorisk-laboratory, 7.9% (n = 323) for Globorisk-office, and 0.3% (n = 5) for SCORE. The models showed poor discrimination and calibration. The performance of SCORE could not be examined because of the limited number of fatal CVD events. SCORE-FNF, the model that is currently used for risk prediction of fatal plus non-fatal CVD in Dutch general practice, was found to underestimate the risk in all deciles of predicted risks. CONCLUSION: Wide eligibility criteria and a broad outcome measure contribute to the model applicability in daily practice. The restriction to fatal CVD outcomes of SCORE renders it less usable in routine Dutch general practice. The models seriously underestimate the 10-year risk of fatal plus non-fatal CVD in Dutch general practice. The poor model performance is possibly because of differences between patients that are eligible for risk prediction and the population that was used for model development. In addition, selection of higher-risk patients for CVD risk assessment by GPs may also contribute to the poor model performance.

Validation of the Dutch version of the primary care resources and support for self-management tool: A tool to assess the quality of self-management support.

INTRODUCTION: Enhancing the self-management activities of patients improves the quality of care and is an integrated element of current healthcare provision. However, self-management support (SMS) is not yet common in healthcare. The Primary Care Resources and Support for Self-Management (PCRS) is a tool for healthcare professionals to assess the quality of SMS. In this study, we assessed the validity and reliability of the Dutch version of the PCRS. METHOD: The validation of the PCRS was performed in Dutch healthcare centres. Correlations between the PCRS scores and the Assessment of Chronic Illness Care (ACIC) and Clinician Support for Patient Activation Measure (CS-PAM) scores were calculated to assess the convergent and discriminant validity. A confirmatory factor analysis (CFA) was performed to test the factor structure. Lastly, the internal consistency and face validity were assessed. RESULTS: The convergent and discriminant validity were good, with respective correlations of 0.730 (p < 0.001) and 0.030 (p > 0.050) between the PCRS and the ACIC SMS subscale and the PCRS and the CS-PAM. Although 49% of the variance of the PCRS was explained by one factor, the CFA could not confirm a fit between a one-factor model and the data. The reliability was excellent (Cronbach's α = 0.921). CONCLUSION: The PCRS showed good validity and excellent internal consistency. However, the evidence for its validity was inconclusive. We therefore suggest rephrasing specific items.

Do self-management interventions in COPD patients work and which patients benefit most? An individual patient data meta-analysis.

BACKGROUND: Self-management interventions are considered effective in patients with COPD, but trials have shown inconsistent results and it is unknown which patients benefit most. This study aimed to summarize the evidence on effectiveness of self-management interventions and identify subgroups of COPD patients who benefit most. METHODS: Randomized trials of self-management interventions between 1985 and 2013 were identified through a systematic literature search. Individual patient data of selected studies were requested from principal investigators and analyzed in an individual patient data meta-analysis using generalized mixed effects models. RESULTS: Fourteen trials representing 3,282 patients were included. Self-management interventions improved health-related quality of life at 12 months (standardized mean difference 0.08, 95% confidence interval [CI] 0.00-0.16) and time to first respiratory-related hospitalization (hazard ratio 0.79, 95% CI 0.66-0.94) and all-cause hospitalization (hazard ratio 0.80, 95% CI 0.69-0.90), but had no effect on mortality. Prespecified subgroup analyses showed that interventions were more effective in males (6-month COPD-related hospitalization: interaction P=0.006), patients with severe lung function (6-month all-cause hospitalization: interaction P=0.016), moderate self-efficacy (12-month COPD-related hospitalization: interaction P=0.036), and high body mass index (6-month COPD-related hospitalization: interaction P=0.028 and 6-month mortality: interaction P=0.026). In none of these subgroups, a consistent effect was shown on all relevant outcomes. CONCLUSION: Self-management interventions exert positive effects in patients with COPD on respiratory-related and all-cause hospitalizations and modest effects on 12-month health-related quality of life, supporting the implementation of self-management strategies in clinical practice. Benefits seem similar across the subgroups studied and limiting self-management interventions to specific patient subgroups cannot be recommended.

Continuity in different care modes and its relationship to quality of life: a randomised controlled trial in patients with COPD.

BACKGROUND: New care modes in primary care may affect patients' experienced continuity of care. AIM: To analyse whether experienced continuity for patients with chronic obstructive pulmonary disease (COPD) changes after different care modes are introduced, and to analyse the relationship between continuity of care and patients' quality of life. DESIGN AND SETTING: Randomised controlled trial with 2-year follow-up in general practice in the Netherlands. METHOD: A total of 180 patients with COPD were randomly assigned to three different care modes: self-management, regular monitoring by a practice nurse, and care provided by the GP at the patient's own initiative (usual care). Experienced continuity of care as personal continuity (proportion of visits with patient's own GP) and team continuity (continuity by the primary healthcare team) was measured using a self-administered patient questionnaire. Quality of life was measured using the Chronic Respiratory Questionnaire. RESULTS: Of the final sample (n = 148), those patients receiving usual care experienced the highest personal continuity, although the chance of not contacting any care provider was also highest in this group (29% versus 2% receiving self-management, and 5% receiving regular monitoring). There were no differences in experienced team continuity in the three care modes. No relationship was found between continuity and changes in quality of life. CONCLUSION: Although personal continuity decreases when new care modes are introduced, no evidence that this affects patients' experienced team continuity or patients' quality of life was found. Patients still experienced smooth, ongoing care, and considered care to be connected. Overall, no evidence was found indicating that the introduction of new care modes in primary care for patients with COPD should be discouraged.